In [ ]:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib.ticker import ScalarFormatter
import seaborn as sb
import warnings
warnings.filterwarnings('ignore', category=FutureWarning)
import zipfile
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pd.set_option('display.max_columns', 700)
pd.set_option('display.max_colwidth', 100)
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pisadict2012 = pd.read_csv('./data/pisadict2012.csv', encoding='latin-1', low_memory=False, index_col=0).T
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pisadict2012
Out[ ]:
| CNT | SUBNATIO | STRATUM | OECD | NC | SCHOOLID | STIDSTD | ST01Q01 | ST02Q01 | ST03Q01 | ST03Q02 | ST04Q01 | ST05Q01 | ST06Q01 | ST07Q01 | ST07Q02 | ST07Q03 | ST08Q01 | ST09Q01 | ST115Q01 | ST11Q01 | ST11Q02 | ST11Q03 | ST11Q04 | ST11Q05 | ST11Q06 | ST13Q01 | ST14Q01 | ST14Q02 | ST14Q03 | ST14Q04 | ST15Q01 | ST17Q01 | ST18Q01 | ST18Q02 | ST18Q03 | ST18Q04 | ST19Q01 | ST20Q01 | ST20Q02 | ST20Q03 | ST21Q01 | ST25Q01 | ST26Q01 | ST26Q02 | ST26Q03 | ST26Q04 | ST26Q05 | ST26Q06 | ST26Q07 | ST26Q08 | ST26Q09 | ST26Q10 | ST26Q11 | ST26Q12 | ST26Q13 | ST26Q14 | ST26Q15 | ST26Q16 | ST26Q17 | ST27Q01 | ST27Q02 | ST27Q03 | ST27Q04 | ST27Q05 | ST28Q01 | ST29Q01 | ST29Q02 | ST29Q03 | ST29Q04 | ST29Q05 | ST29Q06 | ST29Q07 | ST29Q08 | ST35Q01 | ST35Q02 | ST35Q03 | ST35Q04 | ST35Q05 | ST35Q06 | ST37Q01 | ST37Q02 | ST37Q03 | ST37Q04 | ST37Q05 | ST37Q06 | ST37Q07 | ST37Q08 | ST42Q01 | ST42Q02 | ST42Q03 | ST42Q04 | ST42Q05 | ST42Q06 | ST42Q07 | ST42Q08 | ST42Q09 | ST42Q10 | ST43Q01 | ST43Q02 | ST43Q03 | ST43Q04 | ST43Q05 | ST43Q06 | ST44Q01 | ST44Q03 | ST44Q04 | ST44Q05 | ST44Q07 | ST44Q08 | ST46Q01 | ST46Q02 | ST46Q03 | ST46Q04 | ST46Q05 | ST46Q06 | ST46Q07 | ST46Q08 | ST46Q09 | ST48Q01 | ST48Q02 | ST48Q03 | ST48Q04 | ST48Q05 | ST49Q01 | ST49Q02 | ST49Q03 | ST49Q04 | ST49Q05 | ST49Q06 | ST49Q07 | ST49Q09 | ST53Q01 | ST53Q02 | ST53Q03 | ST53Q04 | ST55Q01 | ST55Q02 | ST55Q03 | ST55Q04 | ST57Q01 | ST57Q02 | ST57Q03 | ST57Q04 | ST57Q05 | ST57Q06 | ST61Q01 | ST61Q02 | ST61Q03 | ST61Q04 | ST61Q05 | ST61Q06 | ST61Q07 | ST61Q08 | ST61Q09 | ST62Q01 | ST62Q02 | ST62Q03 | ST62Q04 | ST62Q06 | ST62Q07 | ST62Q08 | ST62Q09 | ST62Q10 | ST62Q11 | ST62Q12 | ST62Q13 | ST62Q15 | ST62Q16 | ST62Q17 | ST62Q19 | ST69Q01 | ST69Q02 | ST69Q03 | ST70Q01 | ST70Q02 | ST70Q03 | ST71Q01 | ST72Q01 | ST73Q01 | ST73Q02 | ST74Q01 | ST74Q02 | ST75Q01 | ST75Q02 | ST76Q01 | ST76Q02 | ST77Q01 | ST77Q02 | ST77Q04 | ST77Q05 | ST77Q06 | ST79Q01 | ST79Q02 | ST79Q03 | ST79Q04 | ST79Q05 | ST79Q06 | ST79Q07 | ST79Q08 | ST79Q10 | ST79Q11 | ST79Q12 | ST79Q15 | ST79Q17 | ST80Q01 | ST80Q04 | ST80Q05 | ST80Q06 | ST80Q07 | ST80Q08 | ST80Q09 | ST80Q10 | ST80Q11 | ST81Q01 | ST81Q02 | ST81Q03 | ST81Q04 | ST81Q05 | ST82Q01 | ST82Q02 | ST82Q03 | ST83Q01 | ST83Q02 | ST83Q03 | ST83Q04 | ST84Q01 | ST84Q02 | ST84Q03 | ST85Q01 | ST85Q02 | ST85Q03 | ST85Q04 | ST86Q01 | ST86Q02 | ST86Q03 | ST86Q04 | ST86Q05 | ST87Q01 | ST87Q02 | ST87Q03 | ST87Q04 | ST87Q05 | ST87Q06 | ST87Q07 | ST87Q08 | ST87Q09 | ST88Q01 | ST88Q02 | ST88Q03 | ST88Q04 | ST89Q02 | ST89Q03 | ST89Q04 | ST89Q05 | ST91Q01 | ST91Q02 | ST91Q03 | ST91Q04 | ST91Q05 | ST91Q06 | ST93Q01 | ST93Q03 | ST93Q04 | ST93Q06 | ST93Q07 | ST94Q05 | ST94Q06 | ST94Q09 | ST94Q10 | ST94Q14 | ST96Q01 | ST96Q02 | ST96Q03 | ST96Q05 | ST101Q01 | ST101Q02 | ST101Q03 | ST101Q05 | ST104Q01 | ST104Q04 | ST104Q05 | ST104Q06 | IC01Q01 | IC01Q02 | IC01Q03 | IC01Q04 | IC01Q05 | IC01Q06 | IC01Q07 | IC01Q08 | IC01Q09 | IC01Q10 | IC01Q11 | IC02Q01 | IC02Q02 | IC02Q03 | IC02Q04 | IC02Q05 | IC02Q06 | IC02Q07 | IC03Q01 | IC04Q01 | IC05Q01 | IC06Q01 | IC07Q01 | IC08Q01 | IC08Q02 | IC08Q03 | IC08Q04 | IC08Q05 | IC08Q06 | IC08Q07 | IC08Q08 | IC08Q09 | IC08Q11 | IC09Q01 | IC09Q02 | IC09Q03 | IC09Q04 | IC09Q05 | IC09Q06 | IC09Q07 | IC10Q01 | IC10Q02 | IC10Q03 | IC10Q04 | IC10Q05 | IC10Q06 | IC10Q07 | IC10Q08 | IC10Q09 | IC11Q01 | IC11Q02 | IC11Q03 | IC11Q04 | IC11Q05 | IC11Q06 | IC11Q07 | IC22Q01 | IC22Q02 | IC22Q04 | IC22Q06 | IC22Q07 | IC22Q08 | EC01Q01 | EC02Q01 | EC03Q01 | EC03Q02 | EC03Q03 | EC03Q04 | EC03Q05 | EC03Q06 | EC03Q07 | EC03Q08 | EC03Q09 | EC03Q10 | EC04Q01A | EC04Q01B | EC04Q01C | EC04Q02A | EC04Q02B | EC04Q02C | EC04Q03A | EC04Q03B | EC04Q03C | EC04Q04A | EC04Q04B | EC04Q04C | EC04Q05A | EC04Q05B | EC04Q05C | EC04Q06A | EC04Q06B | EC04Q06C | EC05Q01 | EC06Q01 | EC07Q01 | EC07Q02 | EC07Q03 | EC07Q04 | EC07Q05 | EC08Q01 | EC08Q02 | EC08Q03 | EC08Q04 | EC09Q03 | EC10Q01 | EC11Q02 | EC11Q03 | EC12Q01 | ST22Q01 | ST23Q01 | ST23Q02 | ST23Q03 | ST23Q04 | ST23Q05 | ST23Q06 | ST23Q07 | ST23Q08 | ST24Q01 | ST24Q02 | ST24Q03 | CLCUSE1 | CLCUSE301 | CLCUSE302 | DEFFORT | QUESTID | BOOKID | EASY | AGE | GRADE | PROGN | ANXMAT | ATSCHL | ATTLNACT | BELONG | BFMJ2 | BMMJ1 | CLSMAN | COBN_F | COBN_M | COBN_S | COGACT | CULTDIST | CULTPOS | DISCLIMA | ENTUSE | ESCS | EXAPPLM | EXPUREM | FAILMAT | FAMCON | FAMCONC | FAMSTRUC | FISCED | HEDRES | HERITCUL | HISCED | HISEI | HOMEPOS | HOMSCH | HOSTCUL | ICTATTNEG | ICTATTPOS | ICTHOME | ICTRES | ICTSCH | IMMIG | INFOCAR | INFOJOB1 | INFOJOB2 | INSTMOT | INTMAT | ISCEDD | ISCEDL | ISCEDO | LANGCOMM | LANGN | LANGRPPD | LMINS | MATBEH | MATHEFF | MATINTFC | MATWKETH | MISCED | MMINS | MTSUP | OCOD1 | OCOD2 | OPENPS | OUTHOURS | PARED | PERSEV | REPEAT | SCMAT | SMINS | STUDREL | SUBNORM | TCHBEHFA | TCHBEHSO | TCHBEHTD | TEACHSUP | TESTLANG | TIMEINT | USEMATH | USESCH | WEALTH | ANCATSCHL | ANCATTLNACT | ANCBELONG | ANCCLSMAN | ANCCOGACT | ANCINSTMOT | ANCINTMAT | ANCMATWKETH | ANCMTSUP | ANCSCMAT | ANCSTUDREL | ANCSUBNORM | PV1MATH | PV2MATH | PV3MATH | PV4MATH | PV5MATH | PV1MACC | PV2MACC | PV3MACC | PV4MACC | PV5MACC | PV1MACQ | PV2MACQ | PV3MACQ | PV4MACQ | PV5MACQ | PV1MACS | PV2MACS | PV3MACS | PV4MACS | PV5MACS | PV1MACU | PV2MACU | PV3MACU | PV4MACU | PV5MACU | PV1MAPE | PV2MAPE | PV3MAPE | PV4MAPE | PV5MAPE | PV1MAPF | PV2MAPF | PV3MAPF | PV4MAPF | PV5MAPF | PV1MAPI | PV2MAPI | PV3MAPI | PV4MAPI | PV5MAPI | PV1READ | PV2READ | PV3READ | PV4READ | PV5READ | PV1SCIE | PV2SCIE | PV3SCIE | PV4SCIE | PV5SCIE | W_FSTUWT | W_FSTR1 | W_FSTR2 | W_FSTR3 | W_FSTR4 | W_FSTR5 | W_FSTR6 | W_FSTR7 | W_FSTR8 | W_FSTR9 | W_FSTR10 | W_FSTR11 | W_FSTR12 | W_FSTR13 | W_FSTR14 | W_FSTR15 | W_FSTR16 | W_FSTR17 | W_FSTR18 | W_FSTR19 | W_FSTR20 | W_FSTR21 | W_FSTR22 | W_FSTR23 | W_FSTR24 | W_FSTR25 | W_FSTR26 | W_FSTR27 | W_FSTR28 | W_FSTR29 | W_FSTR30 | W_FSTR31 | W_FSTR32 | W_FSTR33 | W_FSTR34 | W_FSTR35 | W_FSTR36 | W_FSTR37 | W_FSTR38 | W_FSTR39 | W_FSTR40 | W_FSTR41 | W_FSTR42 | W_FSTR43 | W_FSTR44 | W_FSTR45 | W_FSTR46 | W_FSTR47 | W_FSTR48 | W_FSTR49 | W_FSTR50 | W_FSTR51 | W_FSTR52 | W_FSTR53 | W_FSTR54 | W_FSTR55 | W_FSTR56 | W_FSTR57 | W_FSTR58 | W_FSTR59 | W_FSTR60 | W_FSTR61 | W_FSTR62 | W_FSTR63 | W_FSTR64 | W_FSTR65 | W_FSTR66 | W_FSTR67 | W_FSTR68 | W_FSTR69 | W_FSTR70 | W_FSTR71 | W_FSTR72 | W_FSTR73 | W_FSTR74 | W_FSTR75 | W_FSTR76 | W_FSTR77 | W_FSTR78 | W_FSTR79 | W_FSTR80 | WVARSTRR | VAR_UNIT | SENWGT_STU | VER_STU | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| x | Country code 3-character | Adjudicated sub-region code 7-digit code (3-digit country code + region ID + stratum ID) | Stratum ID 7-character (cnt + region ID + original stratum ID) | OECD country | National Centre 6-digit Code | School ID 7-digit (region ID + stratum ID + 3-digit school ID) | Student ID | International Grade | National Study Programme | Birth - Month | Birth -Year | Gender | Attend <ISCED 0> | Age at <ISCED 1> | Repeat - <ISCED 1> | Repeat - <ISCED 2> | Repeat - <ISCED 3> | Truancy - Late for School | Truancy - Skip whole school day | Truancy - Skip classes within school day | At Home - Mother | At Home - Father | At Home - Brothers | At Home - Sisters | At Home - Grandparents | At Home - Others | Mother<Highest Schooling> | Mother Qualifications - <ISCED level 6> | Mother Qualifications - <ISCED level 5A> | Mother Qualifications - <ISCED level 5B> | Mother Qualifications - <ISCED level 4> | Mother Current Job Status | Father<Highest Schooling> | Father Qualifications - <ISCED level 6> | Father Qualifications - <ISCED level 5A> | Father Qualifications - <ISCED level 5B> | Father Qualifications - <ISCED level 4> | Father Current Job Status | Country of Birth International - Self | Country of Birth International - Mother | Country of Birth International - Father | Age of arrival in <country of test> | International Language at Home | Possessions - desk | Possessions - own room | Possessions - study place | Possessions - computer | Possessions - software | Possessions - Internet | Possessions - literature | Possessions - poetry | Possessions - art | Possessions - textbooks | Possessions - <technical reference books> | Possessions - dictionary | Possessions - dishwasher | Possessions - <DVD> | Possessions - <Country item 1> | Possessions - <Country item 2> | Possessions - <Country item 3> | How many - cellular phones | How many - televisions | How many - computers | How many - cars | How many - rooms bath or shower | How many books at home | Math Interest - Enjoy Reading | Instrumental Motivation - Worthwhile for Work | Math Interest - Look Forward to Lessons | Math Interest - Enjoy Maths | Instrumental Motivation - Worthwhile for Career Chances | Math Interest - Interested | Instrumental Motivation - Important for Future Study | Instrumental Motivation - Helps to Get a Job | Subjective Norms -Friends Do Well in Mathematics | Subjective Norms -Friends Work Hard on Mathematics | Subjective Norms - Friends Enjoy Mathematics Tests | Subjective Norms - Parents Believe Studying Mathematics Is Important | Subjective Norms - Parents Believe Mathematics Is Important for Career | Subjective Norms - Parents Like Mathematics | Math Self-Efficacy - Using a <Train Timetable> | Math Self-Efficacy - Calculating TV Discount | Math Self-Efficacy - Calculating Square Metres of Tiles | Math Self-Efficacy - Understanding Graphs in Newspapers | Math Self-Efficacy - Solving Equation 1 | Math Self-Efficacy - Distance to Scale | Math Self-Efficacy - Solving Equation 2 | Math Self-Efficacy - Calculate Petrol Consumption Rate | Math Anxiety - Worry That It Will Be Difficult | Math Self-Concept - Not Good at Maths | Math Anxiety - Get Very Tense | Math Self-Concept- Get Good <Grades> | Math Anxiety - Get Very Nervous | Math Self-Concept - Learn Quickly | Math Self-Concept - One of Best Subjects | Math Anxiety - Feel Helpless | Math Self-Concept - Understand Difficult Work | Math Anxiety - Worry About Getting Poor <Grades> | Perceived Control - Can Succeed with Enough Effort | Perceived Control - Doing Well is Completely Up to Me | Perceived Control - Family Demands and Problems | Perceived Control - Different Teachers | Perceived Control - If I Wanted I Could Perform Well | Perceived Control - Perform Poorly Regardless | Attributions to Failure - Not Good at Maths Problems | Attributions to Failure - Teacher Did Not Explain Well | Attributions to Failure - Bad Guesses | Attributions to Failure - Material Too Hard | Attributions to Failure - Teacher Didnt Get Students Interested | Attributions to Failure - Unlucky | Math Work Ethic - Homework Completed in Time | Math Work Ethic - Work Hard on Homework | Math Work Ethic - Prepared for Exams | Math Work Ethic - Study Hard for Quizzes | Math Work Ethic - Study Until I Understand Everything | Math Work Ethic - Pay Attention in Classes | Math Work Ethic - Listen in Classes | Math Work Ethic - Avoid Distractions When Studying | Math Work Ethic - Keep Work Organized | Math Intentions - Mathematics vs. Language Courses After School | Math Intentions - Mathematics vs. Science Related Major in College | Math Intentions - Study Harder in Mathematics vs. Language Classes | Math Intentions - Take Maximum Number of Mathematics vs. Science Classes | Math Intentions - Pursuing a Career That Involves Mathematics vs. Science | Math Behaviour - Talk about Maths with Friends | Math Behaviour - Help Friends with Maths | Math Behaviour - <Extracurricular> Activity | Math Behaviour - Participate in Competitions | Math Behaviour - Study More Than 2 Extra Hours a Day | Math Behaviour - Play Chess | Math Behaviour - Computer programming | Math Behaviour - Participate in Math Club | Learning Strategies- Important Parts vs. Existing Knowledge vs. Learn by Heart | Learning Strategies- Improve Understanding vs. New Ways vs. Memory | Learning Strategies - Other Subjects vs. Learning Goals vs. Rehearse Problems | Learning Strategies - Repeat Examples vs. Everyday Applications vs. More Information | Out of school lessons - <test lang> | Out of school lessons - <maths> | Out of school lessons - <science> | Out of school lessons - other | Out-of-School Study Time - Homework | Out-of-School Study Time - Guided Homework | Out-of-School Study Time - Personal Tutor | Out-of-School Study Time - Commercial Company | Out-of-School Study Time - With Parent | Out-of-School Study Time - Computer | Experience with Applied Maths Tasks - Use <Train Timetable> | Experience with Applied Maths Tasks - Calculate Price including Tax | Experience with Applied Maths Tasks - Calculate Square Metres | Experience with Applied Maths Tasks - Understand Scientific Tables | Experience with Pure Maths Tasks - Solve Equation 1 | Experience with Applied Maths Tasks - Use a Map to Calculate Distance | Experience with Pure Maths Tasks - Solve Equation 2 | Experience with Applied Maths Tasks - Calculate Power Consumption Rate | Experience with Applied Maths Tasks - Solve Equation 3 | Familiarity with Math Concepts - Exponential Function | Familiarity with Math Concepts - Divisor | Familiarity with Math Concepts - Quadratic Function | Overclaiming - Proper Number | Familiarity with Math Concepts - Linear Equation | Familiarity with Math Concepts - Vectors | Familiarity with Math Concepts - Complex Number | Familiarity with Math Concepts - Rational Number | Familiarity with Math Concepts - Radicals | Overclaiming - Subjunctive Scaling | Familiarity with Math Concepts - Polygon | Overclaiming - Declarative Fraction | Familiarity with Math Concepts - Congruent Figure | Familiarity with Math Concepts - Cosine | Familiarity with Math Concepts - Arithmetic Mean | Familiarity with Math Concepts - Probability | Min in <class period> - <test lang> | Min in <class period> - <Maths> | Min in <class period> - <Science> | No of <class period> p/wk - <test lang> | No of <class period> p/wk - <Maths> | No of <class period> p/wk - <Science> | No of ALL <class period> a week | Class Size - No of Students in <Test Language> Class | OTL - Algebraic Word Problem in Math Lesson | OTL - Algebraic Word Problem in Tests | OTL - Procedural Task in Math Lesson | OTL - Procedural Task in Tests | OTL - Pure Math Reasoning in Math Lesson | OTL - Pure Math Reasoning in Tests | OTL - Applied Math Reasoning in Math Lesson | OTL - Applied Math Reasoning in Tests | Math Teaching - Teacher shows interest | Math Teaching - Extra help | Math Teaching - Teacher helps | Math Teaching - Teacher continues | Math Teaching - Express opinions | Teacher-Directed Instruction - Sets Clear Goals | Teacher-Directed Instruction - Encourages Thinking and Reasoning | Student Orientation - Differentiates Between Students When Giving Tasks | Student Orientation - Assigns Complex Projects | Formative Assessment - Gives Feedback | Teacher-Directed Instruction - Checks Understanding | Student Orientation - Has Students Work in Small Groups | Teacher-Directed Instruction - Summarizes Previous Lessons | Student Orientation - Plans Classroom Activities | Formative Assessment - Gives Feedback on Strengths and Weaknesses | Formative Assessment - Informs about Expectations | Teacher-Directed Instruction - Informs about Learning Goals | Formative Assessment - Tells How to Get Better | Cognitive Activation - Teacher Encourages to Reflect Problems | Cognitive Activation - Gives Problems that Require to Think | Cognitive Activation - Asks to Use Own Procedures | Cognitive Activation - Presents Problems with No Obvious Solutions | Cognitive Activation - Presents Problems in Different Contexts | Cognitive Activation - Helps Learn from Mistakes | Cognitive Activation - Asks for Explanations | Cognitive Activation - Apply What We Learned | Cognitive Activation - Problems with Multiple Solutions | Disciplinary Climate - Students Dont Listen | Disciplinary Climate - Noise and Disorder | Disciplinary Climate - Teacher Has to Wait Until its Quiet | Disciplinary Climate - Students Dont Work Well | Disciplinary Climate - Students Start Working Late | Vignette Teacher Support -Homework Every Other Day/Back in Time | Vignette Teacher Support - Homework Once a Week/Back in Time | Vignette Teacher Support - Homework Once a Week/Not Back in Time | Teacher Support - Lets Us Know We Have to Work Hard | Teacher Support - Provides Extra Help When Needed | Teacher Support - Helps Students with Learning | Teacher Support - Gives Opportunity to Express Opinions | Vignette Classroom Management - Students Frequently Interrupt/Teacher Arrives Early | Vignette Classroom Management - Students Are Calm/Teacher Arrives on Time | Vignette Classroom Management - Students Frequently Interrupt/Teacher Arrives Late | Classroom Management - Students Listen | Classroom Management - Teacher Keeps Class Orderly | Classroom Management - Teacher Starts On Time | Classroom Management - Wait Long to <Quiet Down> | Student-Teacher Relation - Get Along with Teachers | Student-Teacher Relation - Teachers Are Interested | Student-Teacher Relation - Teachers Listen to Students | Student-Teacher Relation - Teachers Help Students | Student-Teacher Relation - Teachers Treat Students Fair | Sense of Belonging - Feel Like Outsider | Sense of Belonging - Make Friends Easily | Sense of Belonging - Belong at School | Sense of Belonging - Feel Awkward at School | Sense of Belonging - Liked by Other Students | Sense of Belonging - Feel Lonely at School | Sense of Belonging - Feel Happy at School | Sense of Belonging - Things Are Ideal at School | Sense of Belonging - Satisfied at School | Attitude towards School - Does Little to Prepare Me for Life | Attitude towards School - Waste of Time | Attitude towards School - Gave Me Confidence | Attitude towards School- Useful for Job | Attitude toward School - Helps to Get a Job | Attitude toward School - Prepare for College | Attitude toward School - Enjoy Good Grades | Attitude toward School - Trying Hard is Important | Perceived Control - Can Succeed with Enough Effort | Perceived Control - My Choice Whether I Will Be Good | Perceived Control - Problems Prevent from Putting Effort into School | Perceived Control - Different Teachers Would Make Me Try Harder | Perceived Control - Could Perform Well if I Wanted | Perceived Control - Perform Poor Regardless | Perseverance - Give up easily | Perseverance - Put off difficult problems | Perseverance - Remain interested | Perseverance - Continue to perfection | Perseverance - Exceed expectations | Openness for Problem Solving - Can Handle a Lot of Information | Openness for Problem Solving - Quick to Understand | Openness for Problem Solving - Seek Explanations | Openness for Problem Solving - Can Link Facts | Openness for Problem Solving - Like to Solve Complex Problems | Problem Text Message - Press every button | Problem Text Message - Trace steps | Problem Text Message - Manual | Problem Text Message - Ask a friend | Problem Route Selection - Read brochure | Problem Route Selection - Study map | Problem Route Selection - Leave it to brother | Problem Route Selection - Just drive | Problem Ticket Machine - Similarities | Problem Ticket Machine - Try buttons | Problem Ticket Machine - Ask for help | Problem Ticket Machine - Find ticket office | At Home - Desktop Computer | At Home - Portable laptop | At Home - Tablet computer | At Home - Internet connection | At Home - Video games console | At Home - Cell phone w/o Internet | At Home - Cell phone with Internet | At Home - Mp3/Mp4 player | At Home - Printer | At Home - USB (memory) stick | At Home - Ebook reader | At school - Desktop Computer | At school - Portable laptop | At school - Tablet computer | At school - Internet connection | At school - Printer | At school - USB (memory) stick | At school - Ebook reader | First use of computers | First access to Internet | Internet at School | Internet out-of-school - Weekday | Internet out-of-school - Weekend | Out-of-school 8 - One player games. | Out-of-school 8 - ColLabourative games. | Out-of-school 8 - Use email | Out-of-school 8 - Chat on line | Out-of-school 8 - Social networks | Out-of-school 8 - Browse the Internet for fun | Out-of-school 8 - Read news | Out-of-school 8 - Obtain practical information from the Internet | Out-of-school 8 - Download music | Out-of-school 8 - Upload content | Out-of-school 9 - Internet for school | Out-of-school 9 - Email students | Out-of-school 9 - Email teachers | Out-of-school 9 - Download from School | Out-of-school 9 - Announcements | Out-of-school 9 - Homework | Out-of-school 9 - Share school material | At School - Chat on line | At School - Email | At School - Browse for schoolwork | At School - Download from website | At School - Post on website | At School - Simulations | At School - Practice and drilling | At School - Homework | At School - Group work | Maths lessons - Draw graph | Maths lessons - Calculation with numbers | Maths lessons - Geometric figures | Maths lessons - Spreadsheet | Maths lessons - Algebra | Maths lessons - Histograms | Maths lessons - Change in graphs | Attitudes - Useful for schoolwork | Attitudes - Homework more fun | Attitudes - Source of information | Attitudes - Troublesome | Attitudes - Not suitable for schoolwork | Attitudes - Too unreliable | Miss 2 months of <ISCED 1> | Miss 2 months of <ISCED 2> | Future Orientation - Internship | Future Orientation - Work-site visits | Future Orientation - Job fair | Future Orientation - Career advisor at school | Future Orientation - Career advisor outside school | Future Orientation - Questionnaire | Future Orientation - Internet search | Future Orientation - Tour<ISCED 3-5> institution | Future Orientation - web search <ISCED 3-5> prog | Future Orientation - <country specific item> | Acquired skills - Find job info - Yes, at school | Acquired skills - Find job info - Yes, out of school | Acquired skills - Find job info - No, never | Acquired skills - Search for job - Yes, at school | Acquired skills - Search for job - Yes, out of school | Acquired skills - Search for job - No, never | Acquired skills - Write resume - Yes, at school | Acquired skills - Write resume - Yes, out of school | Acquired skills - Write resume - No, never | Acquired skills - Job interview - Yes, at school | Acquired skills - Job interview - Yes, out of school | Acquired skills - Job interview - No, never | Acquired skills - ISCED 3-5 programs - Yes, at school | Acquired skills - ISCED 3-5 programs - Yes, out of school | Acquired skills - ISCED 3-5 programs - No, never | Acquired skills - Student financing - Yes, at school | Acquired skills - Student financing - Yes, out of school | Acquired skills - Student financing - No, never | First language learned | Age started learning <test language> | Language spoken - Mother | Language spoken - Father | Language spoken - Siblings | Language spoken - Best friend | Language spoken - Schoolmates | Activities language - Reading | Activities language - Watching TV | Activities language - Internet surfing | Activities language - Writing emails | Types of support <test language> - remedial lessons | Amount of support <test language> | Attend lessons <heritage language> - focused | Attend lessons <heritage language> - school subjects | Instruction in <heritage language> | Acculturation - Mother Immigrant (Filter) | Acculturation - Enjoy <Host Culture> Friends | Acculturation - Enjoy <Heritage Culture> Friends | Acculturation - Enjoy <Host Culture> Celebrations | Acculturation - Enjoy <Heritage Culture> Celebrations | Acculturation - Spend Time with <Host Culture> Friends | Acculturation - Spend Time with <Heritage Culture> Friends | Acculturation - Participate in <Host Culture> Celebrations | Acculturation - Participate in <Heritage Culture> Celebrations | Acculturation - Perceived Host-Heritage Cultural Differences - Values | Acculturation - Perceived Host-Heritage Cultural Differences - Mother Treatment | Acculturation - Perceived Host-Heritage Cultural Differences - Teacher Treatment | Calculator Use | Effort-real 1 | Effort-real 2 | Difference in Effort | Student Questionnaire Form | Booklet ID | Standard or simplified set of booklets | Age of student | Grade compared to modal grade in country | Unique national study programme code | Mathematics Anxiety | Attitude towards School: Learning Outcomes | Attitude towards School: Learning Activities | Sense of Belonging to School | Father SQ ISEI | Mother SQ ISEI | Mathematics Teacher's Classroom Management | Country of Birth National Categories- Father | Country of Birth National Categories- Mother | Country of Birth National Categories- Self | Cognitive Activation in Mathematics Lessons | Cultural Distance between Host and Heritage Culture | Cultural Possessions | Disciplinary Climate | ICT Entertainment Use | Index of economic, social and cultural status | Experience with Applied Mathematics Tasks at School | Experience with Pure Mathematics Tasks at School | Attributions to Failure in Mathematics | Familiarity with Mathematical Concepts | Familiarity with Mathematical Concepts (Signal Detection Adjusted) | Family Structure | Educational level of father (ISCED) | Home educational resources | Acculturation: Heritage Culture Oriented Strategies | Highest educational level of parents | Highest parental occupational status | Home Possessions | ICT Use at Home for School-related Tasks | Acculturation: Host Culture Oriented Strategies | Attitudes Towards Computers: Limitations of the Computer as a Tool for School Learning | Attitudes Towards Computers: Computer as a Tool for School Learning | ICT Availability at Home | ICT resources | ICT Availability at School | Immigration status | Information about Careers | Information about the Labour Market provided by the School | Information about the Labour Market provided outside of School | Instrumental Motivation for Mathematics | Mathematics Interest | ISCED designation | ISCED level | ISCED orientation | Preference for Heritage Language in Conversations with Family and Friends | Language at home (3-digit code) | Preference for Heritage Language in Language Reception and Production | Learning time (minutes per week) - <test language> | Mathematics Behaviour | Mathematics Self-Efficacy | Mathematics Intentions | Mathematics Work Ethic | Educational level of mother (ISCED) | Learning time (minutes per week)- <Mathematics> | Mathematics Teacher's Support | ISCO-08 Occupation code - Mother | ISCO-08 Occupation code - Father | Openness for Problem Solving | Out-of-School Study Time | Highest parental education in years | Perseverance | Grade Repetition | Mathematics Self-Concept | Learning time (minutes per week) - <Science> | Teacher Student Relations | Subjective Norms in Mathematics | Teacher Behaviour: Formative Assessment | Teacher Behaviour: Student Orientation | Teacher Behaviour: Teacher-directed Instruction | Teacher Support | Language of the test | Time of computer use (mins) | Use of ICT in Mathematic Lessons | Use of ICT at School | Wealth | Attitude towards School: Learning Outcomes (Anchored) | Attitude towards School: Learning Activities (Anchored) | Sense of Belonging to School (Anchored) | Mathematics Teacher's Classroom Management (Anchored) | Cognitive Activation in Mathematics Lessons (Anchored) | Instrumental Motivation for Mathematics (Anchored) | Mathematics Interest (Anchored) | Mathematics Work Ethic (Anchored) | Mathematics Teacher's Support (Anchored) | Mathematics Self-Concept (Anchored) | Teacher Student Relations (Anchored) | Subjective Norms in Mathematics (Anchored) | Plausible value 1 in mathematics | Plausible value 2 in mathematics | Plausible value 3 in mathematics | Plausible value 4 in mathematics | Plausible value 5 in mathematics | Plausible value 1 in content subscale of math - Change and Relationships | Plausible value 2 in content subscale of math - Change and Relationships | Plausible value 3 in content subscale of math - Change and Relationships | Plausible value 4 in content subscale of math - Change and Relationships | Plausible value 5 in content subscale of math - Change and Relationships | Plausible value 1 in content subscale of math - Quantity | Plausible value 2 in content subscale of math - Quantity | Plausible value 3 in content subscale of math - Quantity | Plausible value 4 in content subscale of math - Quantity | Plausible value 5 in content subscale of math - Quantity | Plausible value 1 in content subscale of math - Space and Shape | Plausible value 2 in content subscale of math - Space and Shape | Plausible value 3 in content subscale of math - Space and Shape | Plausible value 4 in content subscale of math - Space and Shape | Plausible value 5 in content subscale of math - Space and Shape | Plausible value 1 in content subscale of math - Uncertainty and Data | Plausible value 2 in content subscale of math - Uncertainty and Data | Plausible value 3 in content subscale of math - Uncertainty and Data | Plausible value 4 in content subscale of math - Uncertainty and Data | Plausible value 5 in content subscale of math - Uncertainty and Data | Plausible value 1 in process subscale of math - Employ | Plausible value 2 in process subscale of math - Employ | Plausible value 3 in process subscale of math - Employ | Plausible value 4 in process subscale of math - Employ | Plausible value 5 in process subscale of math - Employ | Plausible value 1 in process subscale of math - Formulate | Plausible value 2 in process subscale of math - Formulate | Plausible value 3 in process subscale of math - Formulate | Plausible value 4 in process subscale of math - Formulate | Plausible value 5 in process subscale of math - Formulate | Plausible value 1 in process subscale of math - Interpret | Plausible value 2 in process subscale of math - Interpret | Plausible value 3 in process subscale of math - Interpret | Plausible value 4 in process subscale of math - Interpret | Plausible value 5 in process subscale of math - Interpret | Plausible value 1 in reading | Plausible value 2 in reading | Plausible value 3 in reading | Plausible value 4 in reading | Plausible value 5 in reading | Plausible value 1 in science | Plausible value 2 in science | Plausible value 3 in science | Plausible value 4 in science | Plausible value 5 in science | FINAL STUDENT WEIGHT | FINAL STUDENT REPLICATE BRR-FAY WEIGHT1 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT2 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT3 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT4 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT5 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT6 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT7 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT8 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT9 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT10 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT11 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT12 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT13 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT14 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT15 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT16 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT17 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT18 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT19 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT20 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT21 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT22 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT23 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT24 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT25 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT26 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT27 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT28 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT29 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT30 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT31 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT32 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT33 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT34 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT35 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT36 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT37 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT38 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT39 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT40 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT41 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT42 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT43 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT44 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT45 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT46 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT47 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT48 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT49 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT50 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT51 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT52 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT53 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT54 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT55 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT56 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT57 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT58 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT59 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT60 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT61 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT62 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT63 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT64 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT65 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT66 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT67 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT68 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT69 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT70 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT71 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT72 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT73 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT74 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT75 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT76 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT77 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT78 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT79 | FINAL STUDENT REPLICATE BRR-FAY WEIGHT80 | RANDOMIZED FINAL VARIANCE STRATUM (1-80) | RANDOMLY ASSIGNED VARIANCE UNIT | Senate weight - sum of weight within the country is 1000 | Date of the database creation |
In [ ]:
with zipfile.ZipFile('./data/pisa2012.csv.zip', 'r') as zip_ref:
with zip_ref.open('pisa2012.csv') as csv_file:
pisa2012 = pd.read_csv(csv_file, encoding='latin-1', low_memory=False, index_col=0)
In [ ]:
pisa2012.head()
Out[ ]:
| CNT | SUBNATIO | STRATUM | OECD | NC | SCHOOLID | STIDSTD | ST01Q01 | ST02Q01 | ST03Q01 | ST03Q02 | ST04Q01 | ST05Q01 | ST06Q01 | ST07Q01 | ST07Q02 | ST07Q03 | ST08Q01 | ST09Q01 | ST115Q01 | ST11Q01 | ST11Q02 | ST11Q03 | ST11Q04 | ST11Q05 | ST11Q06 | ST13Q01 | ST14Q01 | ST14Q02 | ST14Q03 | ST14Q04 | ST15Q01 | ST17Q01 | ST18Q01 | ST18Q02 | ST18Q03 | ST18Q04 | ST19Q01 | ST20Q01 | ST20Q02 | ST20Q03 | ST21Q01 | ST25Q01 | ST26Q01 | ST26Q02 | ST26Q03 | ST26Q04 | ST26Q05 | ST26Q06 | ST26Q07 | ST26Q08 | ST26Q09 | ST26Q10 | ST26Q11 | ST26Q12 | ST26Q13 | ST26Q14 | ST26Q15 | ST26Q16 | ST26Q17 | ST27Q01 | ST27Q02 | ST27Q03 | ST27Q04 | ST27Q05 | ST28Q01 | ST29Q01 | ST29Q02 | ST29Q03 | ST29Q04 | ST29Q05 | ST29Q06 | ST29Q07 | ST29Q08 | ST35Q01 | ST35Q02 | ST35Q03 | ST35Q04 | ST35Q05 | ST35Q06 | ST37Q01 | ST37Q02 | ST37Q03 | ST37Q04 | ST37Q05 | ST37Q06 | ST37Q07 | ST37Q08 | ST42Q01 | ST42Q02 | ST42Q03 | ST42Q04 | ST42Q05 | ST42Q06 | ST42Q07 | ST42Q08 | ST42Q09 | ST42Q10 | ST43Q01 | ST43Q02 | ST43Q03 | ST43Q04 | ST43Q05 | ST43Q06 | ST44Q01 | ST44Q03 | ST44Q04 | ST44Q05 | ST44Q07 | ST44Q08 | ST46Q01 | ST46Q02 | ST46Q03 | ST46Q04 | ST46Q05 | ST46Q06 | ST46Q07 | ST46Q08 | ST46Q09 | ST48Q01 | ST48Q02 | ST48Q03 | ST48Q04 | ST48Q05 | ST49Q01 | ST49Q02 | ST49Q03 | ST49Q04 | ST49Q05 | ST49Q06 | ST49Q07 | ST49Q09 | ST53Q01 | ST53Q02 | ST53Q03 | ST53Q04 | ST55Q01 | ST55Q02 | ST55Q03 | ST55Q04 | ST57Q01 | ST57Q02 | ST57Q03 | ST57Q04 | ST57Q05 | ST57Q06 | ST61Q01 | ST61Q02 | ST61Q03 | ST61Q04 | ST61Q05 | ST61Q06 | ST61Q07 | ST61Q08 | ST61Q09 | ST62Q01 | ST62Q02 | ST62Q03 | ST62Q04 | ST62Q06 | ST62Q07 | ST62Q08 | ST62Q09 | ST62Q10 | ST62Q11 | ST62Q12 | ST62Q13 | ST62Q15 | ST62Q16 | ST62Q17 | ST62Q19 | ST69Q01 | ST69Q02 | ST69Q03 | ST70Q01 | ST70Q02 | ST70Q03 | ST71Q01 | ST72Q01 | ST73Q01 | ST73Q02 | ST74Q01 | ST74Q02 | ST75Q01 | ST75Q02 | ST76Q01 | ST76Q02 | ST77Q01 | ST77Q02 | ST77Q04 | ST77Q05 | ST77Q06 | ST79Q01 | ST79Q02 | ST79Q03 | ST79Q04 | ST79Q05 | ST79Q06 | ST79Q07 | ST79Q08 | ST79Q10 | ST79Q11 | ST79Q12 | ST79Q15 | ST79Q17 | ST80Q01 | ST80Q04 | ST80Q05 | ST80Q06 | ST80Q07 | ST80Q08 | ST80Q09 | ST80Q10 | ST80Q11 | ST81Q01 | ST81Q02 | ST81Q03 | ST81Q04 | ST81Q05 | ST82Q01 | ST82Q02 | ST82Q03 | ST83Q01 | ST83Q02 | ST83Q03 | ST83Q04 | ST84Q01 | ST84Q02 | ST84Q03 | ST85Q01 | ST85Q02 | ST85Q03 | ST85Q04 | ST86Q01 | ST86Q02 | ST86Q03 | ST86Q04 | ST86Q05 | ST87Q01 | ST87Q02 | ST87Q03 | ST87Q04 | ST87Q05 | ST87Q06 | ST87Q07 | ST87Q08 | ST87Q09 | ST88Q01 | ST88Q02 | ST88Q03 | ST88Q04 | ST89Q02 | ST89Q03 | ST89Q04 | ST89Q05 | ST91Q01 | ST91Q02 | ST91Q03 | ST91Q04 | ST91Q05 | ST91Q06 | ST93Q01 | ST93Q03 | ST93Q04 | ST93Q06 | ST93Q07 | ST94Q05 | ST94Q06 | ST94Q09 | ST94Q10 | ST94Q14 | ST96Q01 | ST96Q02 | ST96Q03 | ST96Q05 | ST101Q01 | ST101Q02 | ST101Q03 | ST101Q05 | ST104Q01 | ST104Q04 | ST104Q05 | ST104Q06 | IC01Q01 | IC01Q02 | IC01Q03 | IC01Q04 | IC01Q05 | IC01Q06 | IC01Q07 | IC01Q08 | IC01Q09 | IC01Q10 | IC01Q11 | IC02Q01 | IC02Q02 | IC02Q03 | IC02Q04 | IC02Q05 | IC02Q06 | IC02Q07 | IC03Q01 | IC04Q01 | IC05Q01 | IC06Q01 | IC07Q01 | IC08Q01 | IC08Q02 | IC08Q03 | IC08Q04 | IC08Q05 | IC08Q06 | IC08Q07 | IC08Q08 | IC08Q09 | IC08Q11 | IC09Q01 | IC09Q02 | IC09Q03 | IC09Q04 | IC09Q05 | IC09Q06 | IC09Q07 | IC10Q01 | IC10Q02 | IC10Q03 | IC10Q04 | IC10Q05 | IC10Q06 | IC10Q07 | IC10Q08 | IC10Q09 | IC11Q01 | IC11Q02 | IC11Q03 | IC11Q04 | IC11Q05 | IC11Q06 | IC11Q07 | IC22Q01 | IC22Q02 | IC22Q04 | IC22Q06 | IC22Q07 | IC22Q08 | EC01Q01 | EC02Q01 | EC03Q01 | EC03Q02 | EC03Q03 | EC03Q04 | EC03Q05 | EC03Q06 | EC03Q07 | EC03Q08 | EC03Q09 | EC03Q10 | EC04Q01A | EC04Q01B | EC04Q01C | EC04Q02A | EC04Q02B | EC04Q02C | EC04Q03A | EC04Q03B | EC04Q03C | EC04Q04A | EC04Q04B | EC04Q04C | EC04Q05A | EC04Q05B | EC04Q05C | EC04Q06A | EC04Q06B | EC04Q06C | EC05Q01 | EC06Q01 | EC07Q01 | EC07Q02 | EC07Q03 | EC07Q04 | EC07Q05 | EC08Q01 | EC08Q02 | EC08Q03 | EC08Q04 | EC09Q03 | EC10Q01 | EC11Q02 | EC11Q03 | EC12Q01 | ST22Q01 | ST23Q01 | ST23Q02 | ST23Q03 | ST23Q04 | ST23Q05 | ST23Q06 | ST23Q07 | ST23Q08 | ST24Q01 | ST24Q02 | ST24Q03 | CLCUSE1 | CLCUSE301 | CLCUSE302 | DEFFORT | QUESTID | BOOKID | EASY | AGE | GRADE | PROGN | ANXMAT | ATSCHL | ATTLNACT | BELONG | BFMJ2 | BMMJ1 | CLSMAN | COBN_F | COBN_M | COBN_S | COGACT | CULTDIST | CULTPOS | DISCLIMA | ENTUSE | ESCS | EXAPPLM | EXPUREM | FAILMAT | FAMCON | FAMCONC | FAMSTRUC | FISCED | HEDRES | HERITCUL | HISCED | HISEI | HOMEPOS | HOMSCH | HOSTCUL | ICTATTNEG | ICTATTPOS | ICTHOME | ICTRES | ICTSCH | IMMIG | INFOCAR | INFOJOB1 | INFOJOB2 | INSTMOT | INTMAT | ISCEDD | ISCEDL | ISCEDO | LANGCOMM | LANGN | LANGRPPD | LMINS | MATBEH | MATHEFF | MATINTFC | MATWKETH | MISCED | MMINS | MTSUP | OCOD1 | OCOD2 | OPENPS | OUTHOURS | PARED | PERSEV | REPEAT | SCMAT | SMINS | STUDREL | SUBNORM | TCHBEHFA | TCHBEHSO | TCHBEHTD | TEACHSUP | TESTLANG | TIMEINT | USEMATH | USESCH | WEALTH | ANCATSCHL | ANCATTLNACT | ANCBELONG | ANCCLSMAN | ANCCOGACT | ANCINSTMOT | ANCINTMAT | ANCMATWKETH | ANCMTSUP | ANCSCMAT | ANCSTUDREL | ANCSUBNORM | PV1MATH | PV2MATH | PV3MATH | PV4MATH | PV5MATH | PV1MACC | PV2MACC | PV3MACC | PV4MACC | PV5MACC | PV1MACQ | PV2MACQ | PV3MACQ | PV4MACQ | PV5MACQ | PV1MACS | PV2MACS | PV3MACS | PV4MACS | PV5MACS | PV1MACU | PV2MACU | PV3MACU | PV4MACU | PV5MACU | PV1MAPE | PV2MAPE | PV3MAPE | PV4MAPE | PV5MAPE | PV1MAPF | PV2MAPF | PV3MAPF | PV4MAPF | PV5MAPF | PV1MAPI | PV2MAPI | PV3MAPI | PV4MAPI | PV5MAPI | PV1READ | PV2READ | PV3READ | PV4READ | PV5READ | PV1SCIE | PV2SCIE | PV3SCIE | PV4SCIE | PV5SCIE | W_FSTUWT | W_FSTR1 | W_FSTR2 | W_FSTR3 | W_FSTR4 | W_FSTR5 | W_FSTR6 | W_FSTR7 | W_FSTR8 | W_FSTR9 | W_FSTR10 | W_FSTR11 | W_FSTR12 | W_FSTR13 | W_FSTR14 | W_FSTR15 | W_FSTR16 | W_FSTR17 | W_FSTR18 | W_FSTR19 | W_FSTR20 | W_FSTR21 | W_FSTR22 | W_FSTR23 | W_FSTR24 | W_FSTR25 | W_FSTR26 | W_FSTR27 | W_FSTR28 | W_FSTR29 | W_FSTR30 | W_FSTR31 | W_FSTR32 | W_FSTR33 | W_FSTR34 | W_FSTR35 | W_FSTR36 | W_FSTR37 | W_FSTR38 | W_FSTR39 | W_FSTR40 | W_FSTR41 | W_FSTR42 | W_FSTR43 | W_FSTR44 | W_FSTR45 | W_FSTR46 | W_FSTR47 | W_FSTR48 | W_FSTR49 | W_FSTR50 | W_FSTR51 | W_FSTR52 | W_FSTR53 | W_FSTR54 | W_FSTR55 | W_FSTR56 | W_FSTR57 | W_FSTR58 | W_FSTR59 | W_FSTR60 | W_FSTR61 | W_FSTR62 | W_FSTR63 | W_FSTR64 | W_FSTR65 | W_FSTR66 | W_FSTR67 | W_FSTR68 | W_FSTR69 | W_FSTR70 | W_FSTR71 | W_FSTR72 | W_FSTR73 | W_FSTR74 | W_FSTR75 | W_FSTR76 | W_FSTR77 | W_FSTR78 | W_FSTR79 | W_FSTR80 | WVARSTRR | VAR_UNIT | SENWGT_STU | VER_STU | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Albania | 80000 | ALB0006 | Non-OECD | Albania | 1 | 1 | 10 | 1.0 | 2 | 1996 | Female | No | 6.0 | No, never | No, never | No, never | None | None | 1.0 | Yes | Yes | Yes | Yes | NaN | NaN | <ISCED level 3A> | No | No | No | No | Other (e.g. home duties, retired) | <ISCED level 3A> | NaN | NaN | NaN | NaN | Working part-time <for pay> | Country of test | Country of test | Country of test | NaN | Language of the test | Yes | No | Yes | No | No | No | No | Yes | No | Yes | No | Yes | No | Yes | 8002 | 8001 | 8002 | Two | One | NaN | NaN | NaN | 0-10 books | Agree | Strongly agree | Agree | Agree | Agree | Agree | Agree | Strongly agree | Disagree | Agree | Disagree | Agree | Agree | Agree | Not at all confident | Not very confident | Confident | Confident | Confident | Not at all confident | Confident | Very confident | Agree | Disagree | Agree | Agree | Agree | Agree | Agree | Disagree | Disagree | Disagree | Agree | Disagree | Disagree | Agree | NaN | Disagree | Likely | Slightly likely | Likely | Likely | Likely | Very Likely | Agree | Agree | Agree | Agree | Agree | Agree | Agree | Agree | Agree | Courses after school Test Language | Major in college Science | Study harder Test Language | Maximum classes Science | Pursuing a career Math | Often | Sometimes | Sometimes | Sometimes | Sometimes | Never or rarely | Never or rarely | Never or rarely | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | Every Lesson | Every Lesson | Every Lesson | Every Lesson | Every Lesson | Never or Hardly Ever | Most Lessons | Never or Hardly Ever | Every Lesson | Most Lessons | Every Lesson | Every Lesson | Every Lesson | Never or Hardly Ever | Most Lessons | Every Lesson | Every Lesson | Every Lesson | Always or almost always | Sometimes | Never or rarely | Always or almost always | Always or almost always | Always or almost always | Always or almost always | Often | Often | Never or Hardly Ever | Never or Hardly Ever | Never or Hardly Ever | Never or Hardly Ever | Never or Hardly Ever | Strongly disagree | Strongly disagree | Strongly disagree | Strongly disagree | Agree | Agree | Agree | Strongly agree | Strongly agree | Disagree | Agree | Strongly disagree | Disagree | Agree | Agree | Strongly disagree | Agree | Agree | Disagree | Agree | Agree | Strongly disagree | Strongly agree | Strongly agree | Strongly disagree | Agree | Strongly disagree | Agree | Agree | Strongly agree | Strongly disagree | Strongly disagree | Agree | Strongly agree | Strongly agree | Strongly agree | Strongly agree | Strongly agree | Strongly agree | Strongly disagree | Disagree | Strongly disagree | Very much like me | Very much like me | Very much like me | Somewhat like me | Very much like me | Somewhat like me | Mostly like me | Mostly like me | Mostly like me | Somewhat like me | definitely do this | definitely do this | definitely do this | definitely do this | 4.0 | 2.0 | 1.0 | 1.0 | 1.0 | 2.0 | 1.0 | 1.0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 99 | 99 | 99 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | A Simple calculator | 99 | 99 | 99 | StQ Form B | booklet 7 | Standard set of booklets | 16.17 | 0.0 | Albania: Upper secondary education | 0.32 | -2.31 | 0.5206 | -1.18 | 76.49 | 79.74 | -1.3771 | Albania | Albania | Albania | 0.6994 | NaN | -0.48 | 1.85 | NaN | NaN | NaN | NaN | 0.6400 | NaN | NaN | 2.0 | ISCED 3A, ISCED 4 | -1.29 | NaN | ISCED 3A, ISCED 4 | NaN | -2.61 | NaN | NaN | NaN | NaN | NaN | -3.16 | NaN | Native | NaN | NaN | NaN | 0.80 | 0.91 | A | ISCED level 3 | General | NaN | Albanian | NaN | NaN | 0.6426 | -0.77 | -0.7332 | 0.2882 | ISCED 3A, ISCED 4 | NaN | -0.9508 | Building architects | Primary school teachers | 0.0521 | NaN | 12.0 | -0.3407 | Did not repeat a <grade> | 0.41 | NaN | -1.04 | -0.0455 | 1.3625 | 0.9374 | 0.4297 | 1.68 | Albanian | NaN | NaN | NaN | -2.92 | -1.8636 | -0.6779 | -0.7351 | -0.7808 | -0.0219 | -0.1562 | 0.0486 | -0.2199 | -0.5983 | -0.0807 | -0.5901 | -0.3346 | 406.8469 | 376.4683 | 344.5319 | 321.1637 | 381.9209 | 325.8374 | 324.2795 | 279.8800 | 267.4170 | 312.5954 | 409.1837 | 388.1524 | 373.3525 | 389.7102 | 415.4152 | 351.5423 | 375.6894 | 341.4161 | 386.5945 | 426.3203 | 396.7207 | 334.4057 | 328.9531 | 339.8582 | 354.6580 | 324.2795 | 345.3108 | 381.1419 | 380.3630 | 346.8687 | 319.6059 | 345.3108 | 360.8895 | 390.4892 | 322.7216 | 290.7852 | 345.3108 | 326.6163 | 407.6258 | 367.1210 | 249.5762 | 254.3420 | 406.8496 | 175.7053 | 218.5981 | 341.7009 | 408.8400 | 348.2283 | 367.8105 | 392.9877 | 8.9096 | 13.1249 | 13.0829 | 4.5315 | 13.0829 | 13.9235 | 13.1249 | 13.1249 | 4.3389 | 4.3313 | 13.7954 | 4.5315 | 4.3313 | 13.7954 | 13.9235 | 4.3389 | 4.3313 | 4.5084 | 4.5084 | 13.7954 | 4.5315 | 13.1249 | 13.0829 | 4.5315 | 13.0829 | 13.9235 | 13.1249 | 13.1249 | 4.3389 | 4.3313 | 13.7954 | 4.5315 | 4.3313 | 13.7954 | 13.9235 | 4.3389 | 4.3313 | 4.5084 | 4.5084 | 13.7954 | 4.5315 | 4.5084 | 4.5315 | 13.0829 | 4.5315 | 4.3313 | 4.5084 | 4.5084 | 13.7954 | 13.9235 | 4.3389 | 13.0829 | 13.9235 | 4.3389 | 4.3313 | 13.7954 | 13.9235 | 13.1249 | 13.1249 | 4.3389 | 13.0829 | 4.5084 | 4.5315 | 13.0829 | 4.5315 | 4.3313 | 4.5084 | 4.5084 | 13.7954 | 13.9235 | 4.3389 | 13.0829 | 13.9235 | 4.3389 | 4.3313 | 13.7954 | 13.9235 | 13.1249 | 13.1249 | 4.3389 | 13.0829 | 19 | 1 | 0.2098 | 22NOV13 |
| 2 | Albania | 80000 | ALB0006 | Non-OECD | Albania | 1 | 2 | 10 | 1.0 | 2 | 1996 | Female | Yes, for more than one year | 7.0 | No, never | No, never | No, never | One or two times | None | 1.0 | Yes | Yes | NaN | Yes | NaN | NaN | <ISCED level 3A> | Yes | Yes | No | No | Working full-time <for pay> | <ISCED level 3A> | No | No | No | No | Working full-time <for pay> | Country of test | Country of test | Country of test | NaN | Language of the test | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | 8001 | 8001 | 8002 | Three or more | Three or more | Three or more | Two | Two | 201-500 books | Disagree | Strongly agree | Disagree | Disagree | Agree | Agree | Disagree | Disagree | Strongly agree | Strongly agree | Disagree | Agree | Disagree | Agree | Confident | Very confident | Very confident | Confident | Very confident | Confident | Very confident | Not very confident | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | Strongly agree | Strongly agree | Strongly disagree | Disagree | Agree | Disagree | Likely | Slightly likely | Slightly likely | Very Likely | Slightly likely | Likely | Agree | Agree | Strongly agree | Strongly agree | Strongly agree | Agree | Agree | Disagree | Agree | Courses after school Math | Major in college Science | Study harder Math | Maximum classes Science | Pursuing a career Science | Sometimes | Often | Always or almost always | Sometimes | Always or almost always | Never or rarely | Never or rarely | Often | relating to known | Improve understanding | in my sleep | Repeat examples | I do not attend <out-of-school time lessons> in this subject | 2 or more but less than 4 hours a week | 2 or more but less than 4 hours a week | Less than 2 hours a week | NaN | NaN | 6.0 | 0.0 | 0.0 | 2.0 | Rarely | Rarely | Frequently | Sometimes | Frequently | Sometimes | Frequently | Never | Frequently | Know it well, understand the concept | Know it well, understand the concept | Heard of it once or twice | Know it well, understand the concept | Know it well, understand the concept | Know it well, understand the concept | Never heard of it | Know it well, understand the concept | Know it well, understand the concept | Never heard of it | Know it well, understand the concept | Heard of it once or twice | Know it well, understand the concept | Know it well, understand the concept | Never heard of it | Heard of it often | 45.0 | 45.0 | 45.0 | 7.0 | 6.0 | 2.0 | NaN | 30.0 | Frequently | Sometimes | Frequently | Frequently | Sometimes | Sometimes | Sometimes | Sometimes | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | Not at all like me | Not at all like me | Mostly like me | Somewhat like me | Very much like me | Somewhat like me | Not much like me | Not much like me | Mostly like me | Not much like me | probably not do this | probably do this | probably not do this | probably do this | 1.0 | 2.0 | 3.0 | 2.0 | 2.0 | 3.0 | 1.0 | 1.0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 99 | 99 | 99 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | A Simple calculator | 99 | 99 | 99 | StQ Form A | booklet 9 | Standard set of booklets | 16.17 | 0.0 | Albania: Upper secondary education | NaN | NaN | NaN | NaN | 15.35 | 23.47 | NaN | Albania | Albania | Albania | NaN | NaN | 1.27 | NaN | NaN | NaN | -0.0681 | 0.7955 | 0.1524 | 0.6387 | -0.08 | 2.0 | ISCED 3A, ISCED 4 | 1.12 | NaN | ISCED 5A, 6 | NaN | 1.41 | NaN | NaN | NaN | NaN | NaN | 1.15 | NaN | Native | NaN | NaN | NaN | -0.39 | 0.00 | A | ISCED level 3 | General | NaN | Albanian | NaN | 315.0 | 1.4702 | 0.34 | -0.2514 | 0.6490 | ISCED 5A, 6 | 270.0 | NaN | Tailors, dressmakers, furriers and hatters | Building construction labourers | -0.9492 | 8.0 | 16.0 | 1.3116 | Did not repeat a <grade> | NaN | 90.0 | NaN | 0.6602 | NaN | NaN | NaN | NaN | Albanian | NaN | NaN | NaN | 0.69 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 486.1427 | 464.3325 | 453.4273 | 472.9008 | 476.0165 | 325.6816 | 419.9330 | 378.6493 | 359.9548 | 384.1019 | 373.1968 | 444.0801 | 456.5431 | 401.2385 | 461.2167 | 366.9653 | 459.6588 | 426.1645 | 423.0488 | 443.3011 | 389.5544 | 438.6275 | 417.5962 | 379.4283 | 438.6275 | 440.1854 | 456.5431 | 486.9216 | 458.1010 | 444.0801 | 411.3647 | 437.8486 | 457.3220 | 454.2063 | 460.4378 | 434.7328 | 448.7537 | 494.7110 | 429.2803 | 434.7328 | 406.2936 | 349.8975 | 400.7334 | 369.7553 | 396.7618 | 548.9929 | 471.5964 | 471.5964 | 443.6218 | 454.8116 | 8.9096 | 13.1249 | 13.0829 | 4.5315 | 13.0829 | 13.9235 | 13.1249 | 13.1249 | 4.3389 | 4.3313 | 13.7954 | 4.5315 | 4.3313 | 13.7954 | 13.9235 | 4.3389 | 4.3313 | 4.5084 | 4.5084 | 13.7954 | 4.5315 | 13.1249 | 13.0829 | 4.5315 | 13.0829 | 13.9235 | 13.1249 | 13.1249 | 4.3389 | 4.3313 | 13.7954 | 4.5315 | 4.3313 | 13.7954 | 13.9235 | 4.3389 | 4.3313 | 4.5084 | 4.5084 | 13.7954 | 4.5315 | 4.5084 | 4.5315 | 13.0829 | 4.5315 | 4.3313 | 4.5084 | 4.5084 | 13.7954 | 13.9235 | 4.3389 | 13.0829 | 13.9235 | 4.3389 | 4.3313 | 13.7954 | 13.9235 | 13.1249 | 13.1249 | 4.3389 | 13.0829 | 4.5084 | 4.5315 | 13.0829 | 4.5315 | 4.3313 | 4.5084 | 4.5084 | 13.7954 | 13.9235 | 4.3389 | 13.0829 | 13.9235 | 4.3389 | 4.3313 | 13.7954 | 13.9235 | 13.1249 | 13.1249 | 4.3389 | 13.0829 | 19 | 1 | 0.2098 | 22NOV13 |
| 3 | Albania | 80000 | ALB0006 | Non-OECD | Albania | 1 | 3 | 9 | 1.0 | 9 | 1996 | Female | Yes, for more than one year | 6.0 | No, never | No, never | No, never | None | None | 1.0 | Yes | Yes | No | Yes | No | No | <ISCED level 3B, 3C> | Yes | Yes | Yes | No | Working full-time <for pay> | <ISCED level 3A> | Yes | No | Yes | Yes | Working full-time <for pay> | Country of test | Country of test | Country of test | NaN | Language of the test | Yes | Yes | Yes | Yes | No | Yes | Yes | Yes | Yes | Yes | No | Yes | No | Yes | 8001 | 8001 | 8001 | Three or more | Two | Two | One | Two | More than 500 books | Agree | Strongly agree | Agree | Agree | Strongly agree | Strongly agree | Strongly agree | Strongly agree | Strongly agree | Strongly agree | Agree | Strongly agree | Strongly agree | Agree | Confident | Very confident | Very confident | Confident | Very confident | Not very confident | Very confident | Confident | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | Strongly agree | Agree | Strongly agree | Strongly disagree | Strongly agree | Strongly disagree | Likely | Likely | Very Likely | Very Likely | Very Likely | Slightly likely | Strongly agree | Strongly agree | Strongly agree | Strongly agree | Strongly agree | Agree | Strongly agree | Strongly agree | Strongly agree | Courses after school Math | Major in college Science | Study harder Math | Maximum classes Science | Pursuing a career Science | Sometimes | Always or almost always | Sometimes | Never or rarely | Always or almost always | Never or rarely | Never or rarely | Never or rarely | Most important | Improve understanding | learning goals | more information | Less than 2 hours a week | 2 or more but less than 4 hours a week | 4 or more but less than 6 hours a week | I do not attend <out-of-school time lessons> in this subject | NaN | 6.0 | 6.0 | 7.0 | 2.0 | 3.0 | Frequently | Sometimes | Frequently | Rarely | Frequently | Rarely | Frequently | Sometimes | Frequently | Never heard of it | Know it well, understand the concept | Heard of it once or twice | Know it well, understand the concept | Know it well, understand the concept | Know it well, understand the concept | Heard of it once or twice | Know it well, understand the concept | Know it well, understand the concept | Heard of it once or twice | Know it well, understand the concept | Know it well, understand the concept | Know it well, understand the concept | Know it well, understand the concept | Know it well, understand the concept | Know it well, understand the concept | 60.0 | NaN | NaN | 5.0 | 4.0 | 2.0 | 24.0 | 30.0 | Frequently | Frequently | Frequently | Frequently | Frequently | Frequently | Rarely | Rarely | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | Not much like me | Not much like me | Very much like me | Very much like me | Somewhat like me | Mostly like me | Mostly like me | Very much like me | Mostly like me | Very much like me | probably not do this | definitely do this | definitely not do this | probably do this | 1.0 | 3.0 | 4.0 | 1.0 | 3.0 | 4.0 | 1.0 | 1.0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 99 | 99 | 99 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | A Simple calculator | 99 | 99 | 99 | StQ Form A | booklet 3 | Standard set of booklets | 15.58 | -1.0 | Albania: Lower secondary education | NaN | NaN | NaN | NaN | 22.57 | NaN | NaN | Albania | Albania | Albania | NaN | NaN | 1.27 | NaN | NaN | NaN | 0.5359 | 0.7955 | 1.2219 | 0.8215 | -0.89 | 2.0 | ISCED 5A, 6 | -0.69 | NaN | ISCED 5A, 6 | NaN | 0.14 | NaN | NaN | NaN | NaN | NaN | -0.40 | NaN | Native | NaN | NaN | NaN | 1.59 | 1.23 | A | ISCED level 2 | General | NaN | Albanian | NaN | 300.0 | 0.9618 | 0.34 | -0.2514 | 2.0389 | ISCED 5A, 6 | NaN | NaN | Housewife | Bricklayers and related workers | 0.9383 | 24.0 | 16.0 | 0.9918 | Did not repeat a <grade> | NaN | NaN | NaN | 2.2350 | NaN | NaN | NaN | NaN | Albanian | NaN | NaN | NaN | -0.23 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 533.2684 | 481.0796 | 489.6479 | 490.4269 | 533.2684 | 611.1622 | 486.5322 | 567.5417 | 541.0578 | 544.9525 | 597.1413 | 495.1005 | 576.8889 | 507.5635 | 556.6365 | 594.8045 | 473.2902 | 554.2997 | 537.1631 | 568.3206 | 471.7324 | 431.2276 | 460.8272 | 419.5435 | 456.9325 | 559.7523 | 501.3320 | 555.0787 | 467.0587 | 506.7845 | 580.7836 | 481.0796 | 555.0787 | 453.8168 | 491.2058 | 527.0369 | 444.4695 | 516.1318 | 403.9648 | 476.4060 | 401.2100 | 404.3872 | 387.7067 | 431.3938 | 401.2100 | 499.6643 | 428.7952 | 492.2044 | 512.7191 | 499.6643 | 8.4871 | 12.7307 | 12.7307 | 4.2436 | 12.7307 | 12.7307 | 12.7307 | 12.7307 | 4.2436 | 4.2436 | 12.7307 | 4.2436 | 4.2436 | 12.7307 | 12.7307 | 4.2436 | 4.2436 | 4.2436 | 4.2436 | 12.7307 | 4.2436 | 12.7307 | 12.7307 | 4.2436 | 12.7307 | 12.7307 | 12.7307 | 12.7307 | 4.2436 | 4.2436 | 12.7307 | 4.2436 | 4.2436 | 12.7307 | 12.7307 | 4.2436 | 4.2436 | 4.2436 | 4.2436 | 12.7307 | 4.2436 | 4.2436 | 4.2436 | 12.7307 | 4.2436 | 4.2436 | 4.2436 | 4.2436 | 12.7307 | 12.7307 | 4.2436 | 12.7307 | 12.7307 | 4.2436 | 4.2436 | 12.7307 | 12.7307 | 12.7307 | 12.7307 | 4.2436 | 12.7307 | 4.2436 | 4.2436 | 12.7307 | 4.2436 | 4.2436 | 4.2436 | 4.2436 | 12.7307 | 12.7307 | 4.2436 | 12.7307 | 12.7307 | 4.2436 | 4.2436 | 12.7307 | 12.7307 | 12.7307 | 12.7307 | 4.2436 | 12.7307 | 19 | 1 | 0.1999 | 22NOV13 |
| 4 | Albania | 80000 | ALB0006 | Non-OECD | Albania | 1 | 4 | 9 | 1.0 | 8 | 1996 | Female | Yes, for more than one year | 6.0 | No, never | No, never | No, never | None | None | 1.0 | Yes | Yes | No | Yes | No | No | <ISCED level 3B, 3C> | No | No | No | No | Working full-time <for pay> | <ISCED level 3A> | Yes | Yes | No | No | Working full-time <for pay> | Country of test | Country of test | Country of test | NaN | Language of the test | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | No | Yes | Yes | No | 8001 | 8001 | 8002 | Three or more | Two | One | NaN | One | 11-25 books | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | Strongly agree | Disagree | Agree | Agree | Disagree | Strongly agree | Disagree | Agree | Agree | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | relating to known | new ways | learning goals | more information | I do not attend <out-of-school time lessons> in this subject | I do not attend <out-of-school time lessons> in this subject | Less than 2 hours a week | I do not attend <out-of-school time lessons> in this subject | 10.0 | 2.0 | 2.0 | 0.0 | 0.0 | 3.0 | Sometimes | Sometimes | Sometimes | Sometimes | Frequently | Sometimes | Frequently | Rarely | Frequently | Heard of it often | Heard of it often | Heard of it often | Know it well, understand the concept | Heard of it a few times | Know it well, understand the concept | Never heard of it | Know it well, understand the concept | Know it well, understand the concept | Never heard of it | Know it well, understand the concept | Never heard of it | Know it well, understand the concept | Know it well, understand the concept | Heard of it often | Heard of it often | 45.0 | 45.0 | 45.0 | 3.0 | 3.0 | 2.0 | NaN | 28.0 | Frequently | Sometimes | Frequently | Rarely | Frequently | Frequently | Sometimes | Sometimes | Every Lesson | Every Lesson | Every Lesson | Every Lesson | Every Lesson | NaN | Every Lesson | Every Lesson | Every Lesson | Every Lesson | Every Lesson | Every Lesson | Every Lesson | Every Lesson | Never or Hardly Ever | Most Lessons | Every Lesson | Every Lesson | Always or almost always | NaN | NaN | NaN | NaN | NaN | NaN | NaN | Never or rarely | Never or Hardly Ever | Never or Hardly Ever | Never or Hardly Ever | Never or Hardly Ever | NaN | NaN | NaN | Strongly agree | Strongly agree | Strongly agree | Strongly agree | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 99 | 99 | 99 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 99 | 99 | 99 | StQ Form C | booklet 2 | Standard set of booklets | 15.67 | -1.0 | Albania: Lower secondary education | 0.31 | NaN | NaN | NaN | 14.21 | NaN | NaN | Albania | Albania | Albania | -0.3788 | NaN | 1.27 | 1.80 | NaN | NaN | 0.3220 | 0.7955 | NaN | 0.7266 | 0.24 | 2.0 | ISCED 5A, 6 | 0.04 | NaN | ISCED 5A, 6 | NaN | -0.73 | NaN | NaN | NaN | NaN | NaN | -0.40 | NaN | Native | NaN | NaN | NaN | NaN | NaN | A | ISCED level 2 | General | NaN | Albanian | NaN | 135.0 | NaN | NaN | NaN | NaN | ISCED 3B, C | 135.0 | 1.6748 | Housewife | Cleaners and helpers in offices, hotels and other establishm | NaN | 17.0 | 16.0 | NaN | Did not repeat a <grade> | 0.18 | 90.0 | NaN | NaN | 0.7644 | 3.3108 | 2.3916 | 1.68 | Albanian | NaN | NaN | NaN | -1.17 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 412.2215 | 498.6836 | 415.3373 | 466.7472 | 454.2842 | 538.4094 | 511.9255 | 553.9882 | 483.8838 | 479.2102 | 525.1675 | 529.0622 | 539.1883 | 516.5992 | 501.7993 | 658.3658 | 567.2301 | 669.2709 | 652.1343 | 645.1239 | 508.0308 | 522.0517 | 524.3885 | 495.5678 | 458.1788 | 524.3885 | 462.0735 | 494.0100 | 459.7367 | 471.4208 | 534.5147 | 455.8420 | 504.1362 | 454.2842 | 483.8838 | 521.2728 | 481.5470 | 503.3572 | 469.8629 | 478.4312 | 547.3630 | 481.4353 | 461.5776 | 425.0393 | 471.9036 | 438.6796 | 481.5740 | 448.9370 | 474.1141 | 426.5573 | 8.4871 | 12.7307 | 12.7307 | 4.2436 | 12.7307 | 12.7307 | 12.7307 | 12.7307 | 4.2436 | 4.2436 | 12.7307 | 4.2436 | 4.2436 | 12.7307 | 12.7307 | 4.2436 | 4.2436 | 4.2436 | 4.2436 | 12.7307 | 4.2436 | 12.7307 | 12.7307 | 4.2436 | 12.7307 | 12.7307 | 12.7307 | 12.7307 | 4.2436 | 4.2436 | 12.7307 | 4.2436 | 4.2436 | 12.7307 | 12.7307 | 4.2436 | 4.2436 | 4.2436 | 4.2436 | 12.7307 | 4.2436 | 4.2436 | 4.2436 | 12.7307 | 4.2436 | 4.2436 | 4.2436 | 4.2436 | 12.7307 | 12.7307 | 4.2436 | 12.7307 | 12.7307 | 4.2436 | 4.2436 | 12.7307 | 12.7307 | 12.7307 | 12.7307 | 4.2436 | 12.7307 | 4.2436 | 4.2436 | 12.7307 | 4.2436 | 4.2436 | 4.2436 | 4.2436 | 12.7307 | 12.7307 | 4.2436 | 12.7307 | 12.7307 | 4.2436 | 4.2436 | 12.7307 | 12.7307 | 12.7307 | 12.7307 | 4.2436 | 12.7307 | 19 | 1 | 0.1999 | 22NOV13 |
| 5 | Albania | 80000 | ALB0006 | Non-OECD | Albania | 1 | 5 | 9 | 1.0 | 10 | 1996 | Female | Yes, for more than one year | 6.0 | No, never | No, never | No, never | One or two times | None | 2.0 | Yes | Yes | Yes | NaN | NaN | NaN | She did not complete <ISCED level 1> | No | No | No | No | Working part-time <for pay> | <ISCED level 3B, 3C> | No | No | No | Yes | Working part-time <for pay> | Country of test | Country of test | Country of test | NaN | Language of the test | Yes | Yes | No | Yes | Yes | Yes | Yes | Yes | Yes | Yes | No | Yes | Yes | Yes | 8001 | 8002 | 8001 | Two | One | Two | NaN | One | 101-200 books | Disagree | Strongly agree | Disagree | Disagree | Strongly agree | Strongly agree | Strongly agree | Strongly agree | Strongly agree | Strongly agree | Strongly agree | Strongly agree | Strongly agree | Agree | Confident | Very confident | NaN | Very confident | Very confident | Confident | Very confident | Not very confident | Strongly agree | Strongly agree | Agree | Strongly agree | Strongly agree | Disagree | Disagree | Disagree | Agree | Agree | Strongly agree | Strongly agree | Disagree | Disagree | Strongly agree | Disagree | Likely | Likely | Likely | Likely | Slightly likely | Very Likely | Strongly agree | Strongly agree | Agree | Strongly agree | Strongly agree | Agree | Strongly agree | Strongly agree | Strongly agree | Courses after school Test Language | Major in college Math | Study harder Math | Maximum classes Math | Pursuing a career Math | Always or almost always | Always or almost always | Often | Often | Sometimes | NaN | Sometimes | Sometimes | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | Every Lesson | Most Lessons | Every Lesson | Most Lessons | Some Lessons | Some Lessons | Some Lessons | Most Lessons | Some Lessons | Most Lessons | Every Lesson | Most Lessons | Every Lesson | Some Lessons | Most Lessons | Most Lessons | Every Lesson | Most Lessons | Always or almost always | Often | Sometimes | Often | Often | Often | Always or almost always | Often | Often | Some Lessons | Some Lessons | NaN | Most Lessons | Never or Hardly Ever | Strongly disagree | Disagree | Strongly agree | Strongly agree | Agree | Strongly agree | Agree | Disagree | Strongly agree | Disagree | Agree | Agree | Strongly agree | Agree | Agree | Agree | Agree | Agree | Agree | Strongly disagree | Strongly agree | Strongly agree | Strongly disagree | Strongly agree | Strongly disagree | Strongly agree | Strongly agree | Strongly agree | Disagree | Strongly disagree | Strongly agree | Strongly agree | Strongly agree | Strongly agree | Strongly agree | Strongly agree | Agree | Strongly agree | Strongly disagree | Agree | Strongly agree | Disagree | NaN | Mostly like me | Very much like me | Very much like me | Very much like me | Very much like me | Very much like me | Mostly like me | Very much like me | Mostly like me | definitely do this | definitely do this | definitely do this | definitely do this | 1.0 | 2.0 | 1.0 | 2.0 | 1.0 | 2.0 | 1.0 | 1.0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 99 | 99 | 99 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 99 | 99 | 99 | StQ Form B | booklet 4 | Standard set of booklets | 15.50 | -1.0 | Albania: Lower secondary education | 1.02 | 1.38 | 1.2115 | 2.63 | 80.92 | NaN | -0.0784 | Albania | Albania | Albania | 0.5403 | NaN | 1.27 | -0.08 | NaN | NaN | NaN | NaN | 0.6400 | NaN | NaN | 2.0 | ISCED 3A, ISCED 4 | -0.69 | NaN | ISCED 3A, ISCED 4 | NaN | -0.57 | NaN | NaN | NaN | NaN | NaN | 0.24 | NaN | Native | NaN | NaN | NaN | 1.59 | 0.30 | A | ISCED level 2 | General | NaN | Albanian | NaN | NaN | 1.8169 | 0.41 | 0.6584 | 1.6881 | NaN | NaN | 0.6709 | Housewife | Economists | 1.2387 | NaN | 12.0 | 1.0819 | Did not repeat a <grade> | -0.06 | NaN | -0.02 | 2.8039 | 0.7644 | 0.9374 | 0.4297 | 0.11 | Albanian | NaN | NaN | NaN | -1.17 | 0.6517 | 0.4908 | 0.8675 | 0.0505 | 0.4940 | 0.9986 | 0.0486 | 0.9341 | 0.4052 | 0.0358 | 0.2492 | 1.2260 | 381.9209 | 328.1742 | 403.7311 | 418.5309 | 395.1628 | 373.3525 | 293.1220 | 364.0053 | 430.2150 | 403.7311 | 414.6362 | 385.8155 | 392.8260 | 448.9095 | 474.6144 | 417.7520 | 353.1002 | 424.7624 | 457.4778 | 459.0357 | 339.0793 | 309.4797 | 340.6372 | 369.4579 | 384.2577 | 373.3525 | 392.0470 | 347.6476 | 342.1950 | 342.1950 | 432.5518 | 431.7729 | 399.0575 | 369.4579 | 341.4161 | 297.0167 | 353.8791 | 347.6476 | 314.1533 | 311.0375 | 311.7707 | 141.7883 | 293.5015 | 272.8495 | 260.1405 | 361.5628 | 275.7740 | 372.7527 | 403.5248 | 422.1746 | 8.4871 | 12.7307 | 12.7307 | 4.2436 | 12.7307 | 12.7307 | 12.7307 | 12.7307 | 4.2436 | 4.2436 | 12.7307 | 4.2436 | 4.2436 | 12.7307 | 12.7307 | 4.2436 | 4.2436 | 4.2436 | 4.2436 | 12.7307 | 4.2436 | 12.7307 | 12.7307 | 4.2436 | 12.7307 | 12.7307 | 12.7307 | 12.7307 | 4.2436 | 4.2436 | 12.7307 | 4.2436 | 4.2436 | 12.7307 | 12.7307 | 4.2436 | 4.2436 | 4.2436 | 4.2436 | 12.7307 | 4.2436 | 4.2436 | 4.2436 | 12.7307 | 4.2436 | 4.2436 | 4.2436 | 4.2436 | 12.7307 | 12.7307 | 4.2436 | 12.7307 | 12.7307 | 4.2436 | 4.2436 | 12.7307 | 12.7307 | 12.7307 | 12.7307 | 4.2436 | 12.7307 | 4.2436 | 4.2436 | 12.7307 | 4.2436 | 4.2436 | 4.2436 | 4.2436 | 12.7307 | 12.7307 | 4.2436 | 12.7307 | 12.7307 | 4.2436 | 4.2436 | 12.7307 | 12.7307 | 12.7307 | 12.7307 | 4.2436 | 12.7307 | 19 | 1 | 0.1999 | 22NOV13 |
In [ ]:
pisa2012.info()
<class 'pandas.core.frame.DataFrame'> Index: 485490 entries, 1 to 485490 Columns: 635 entries, CNT to VER_STU dtypes: float64(250), int64(17), object(368) memory usage: 2.3+ GB
In [ ]:
', '.join(pisa2012.NC.unique())
Out[ ]:
'Albania, United Arab Emirates , Argentina, Australia, Austria, Belgium, Bulgaria , Brazil , Canada , Switzerland, Chile, Colombia , Costa Rica , Czech Republic , Germany, Denmark, Spain, Estonia, Finland, France , United Kingdom (excl.Scotland) , United Kingdom (Scotland), Greece , Hong Kong-China, Croatia, Hungary, Indonesia, Ireland, Iceland, Israel , Italy, Jordan , Japan, Kazakhstan , Republic of Korea, Liechtenstein, Lithuania, Luxembourg , Latvia , Macao-China, Mexico , Montenegro , Malaysia , Netherlands, Norway , New Zealand, Peru , Poland , Portugal , Qatar, China (Shanghai) , Perm (Russian Federation), United States of America , Romania, Russian Federation , Singapore, Serbia , Slovak Republic, Slovenia , Sweden , Chinese Taipei , Thailand , Tunisia, Turkey , Uruguay, Viet Nam '
In [ ]:
dummy_columns = ['NC', 'ST03Q01', 'ST03Q02', 'ST04Q01',
'PV1MATH', 'PV2MATH', 'PV3MATH', 'PV4MATH', 'PV5MATH',
'PV1READ', 'PV2READ', 'PV3READ', 'PV4READ', 'PV5READ',
'PV1SCIE', 'PV2SCIE', 'PV3SCIE', 'PV4SCIE', 'PV5SCIE']
dict = {
'AGE': 'Age',
'HISEI': 'Occupational',
'PARED': 'Education',
'HOMEPOS': 'Home Setup',
'ESCS': 'Socioeconomic'
}
NC_renaming = {
"United Kingdom (excl.Scotland)": "United Kingdom",
"United Kingdom (Scotland)": "United Kingdom",
"Hong Kong-China": "Greater China\n (excl.Mainland)",
"Macao-China": "Greater China\n (excl.Mainland)",
"China (Shanghai)": "Greater China\n (excl.Mainland)",
"Perm (Russian Federation)": "Russian Federation",
"United States of America" :"USA",
"Singapore": "Greater China\n (excl.Mainland)",
"Chinese Taipei": "Greater China\n (excl.Mainland)"
}
selected_columns = list(dict.keys()) + dummy_columns
pisadict2012clean = pisadict2012[selected_columns].rename(columns=dict)
pisa2012clean = pisa2012[selected_columns].rename(columns=dict)
In [ ]:
Dependencies = ['Education', 'Occupational', 'Home Setup']
Subjects = ['Math', 'Reading', 'Science']
In [ ]:
pisa2012clean['Country'] = pisa2012clean['NC'].str.rstrip().replace(NC_renaming)
pisa2012clean['Male'] = pisa2012clean['ST04Q01'].map({'Male': 1, 'Female': 0})
pisa2012clean['Math'] = pisa2012clean[[f'PV{i}MATH' for i in range(1, 6)]].mean(axis=1)
pisa2012clean['Reading'] = pisa2012clean[[f'PV{i}READ' for i in range(1, 6)]].mean(axis=1)
pisa2012clean['Science'] = pisa2012clean[[f'PV{i}SCIE' for i in range(1, 6)]].mean(axis=1)
pisa2012clean['Total'] = pisa2012clean[Subjects].mean(axis=1)
In [ ]:
pisadict2012clean = pisadict2012clean.loc[:, ~pisadict2012clean.columns.isin(dummy_columns)]
pisa2012clean = pisa2012clean.loc[:, ~pisa2012clean.columns.isin(dummy_columns)]
In [ ]:
Total_mean = pisa2012clean.groupby('Country')['Total'].mean()
order = Total_mean.sort_values(ascending=False).index.tolist()
In [ ]:
pisadict2012clean.T
Out[ ]:
| x | |
|---|---|
| Age | Age of student |
| Occupational | Highest parental occupational status |
| Education | Highest parental education in years |
| Home Setup | Home Possessions |
| Socioeconomic | Index of economic, social and cultural status |
In [ ]:
pisa2012clean.info()
<class 'pandas.core.frame.DataFrame'> Index: 485490 entries, 1 to 485490 Data columns (total 11 columns): # Column Non-Null Count Dtype --- ------ -------------- ----- 0 Age 485374 non-null float64 1 Occupational 450621 non-null float64 2 Education 473091 non-null float64 3 Home Setup 479807 non-null float64 4 Socioeconomic 473648 non-null float64 5 Country 485490 non-null object 6 Male 485490 non-null int64 7 Math 485490 non-null float64 8 Reading 485490 non-null float64 9 Science 485490 non-null float64 10 Total 485490 non-null float64 dtypes: float64(9), int64(1), object(1) memory usage: 44.4+ MB
How is total performance distributed among participants?¶
In [ ]:
# Creating a histogram to visualize the distribution of total performance
plt.figure(figsize=(10, 6))
sb.histplot(pisa2012clean['Total'], kde=True, bins=30, color='skyblue')
# Setting the title, x-axis label, and y-axis label
plt.title('Distribution of Total Performance')
plt.xlabel('Total Performance')
plt.ylabel('Number of Participants');
It shows the frequency distribution of participants' total performance scores, suggesting a roughly normal distribution with a peak around the 400-500 range.¶
What is the distribution of educational levels among participants?¶
In [ ]:
plt.figure(figsize=(10, 6))
# Plotting the histogram of educational levels
sb.histplot(pisa2012clean['Education'], bins=20, color='purple')
# Setting the title, x-axis label, and y-axis label
plt.title('Distribution of Educational Levels')
plt.xlabel('Years of Education')
plt.ylabel('Number of Participants');
This histogram displays the count of participants according to the number of years of education they have completed, with notable peaks at 12 and 16 years, suggesting high school and college education levels respectively.¶
What is the age distribution of participants?¶
In [ ]:
# Plotting the histogram of age distribution
plt.figure(figsize=(10, 6))
sb.histplot(pisa2012clean['Age'], bins=30, color='green')
# Setting the title, x-axis label, and y-axis label
plt.title('Age Distribution of Participants')
plt.xlabel('Age')
plt.ylabel('Number of Participants');
The histogram shows that participant ages are concentrated around 15-16 years, which could indicate a study involving high school students.¶
Is there a difference in math performance between genders?¶
In [ ]:
# Creating a boxplot to visualize math performance by gender
plt.figure(figsize=(10, 6))
sb.boxplot(x='Male', y='Math', data=pisa2012clean, palette='pastel')
# Setting the title, x-axis label, and y-axis label
plt.title('Math Performance by Gender')
plt.xlabel('Gender (0 = Female, 1 = Male)')
plt.ylabel('Math Performance');
The box plot compares the distribution of math performance scores between male (1) and female (0) participants. It indicates median performance and the range of scores for each gender.¶
How does math performance vary across different age groups?¶
In [ ]:
# Plotting boxplot for Math performance by Age groups
plt.figure(figsize=(12, 8))
sb.boxplot(x='Age', y='Math', data=pisa2012clean, color='blue')
# Setting the title, x-axis label, and y-axis label
plt.title('Math Performance by Age Groups')
plt.xlabel('Age')
plt.ylabel('Math Performance')
# Rotating x-axis labels for better readability
plt.xticks(rotation=45);
It provides a box plot for each age group, showing the central tendency and spread of math performance within those groups.¶
Is there a correlation between socioeconomic status and total performance¶
In [ ]:
# Create scatter plot
plt.figure(figsize=(10, 6))
sb.scatterplot(x='Socioeconomic', y='Total', data=pisa2012clean, hue='Male', palette='coolwarm', alpha=.6)
# Set title and axis labels
plt.title('Relationship Between Socioeconomic Status and Total Performance')
plt.xlabel('Socioeconomic Index')
plt.ylabel('Total Performance');
The scatter plot depicts individual data points representing participants, colored by gender, against socioeconomic index scores and their corresponding total performance.¶
What is the average socioeconomic status in each country?¶
In [ ]:
# Calculating the average socioeconomic status by country and sorting the values
average_socioeconomic_by_country = pisa2012clean.groupby('Country')['Socioeconomic'].mean().sort_values()
# Plotting the bar chart
plt.figure(figsize=(25, 8))
average_socioeconomic_by_country.plot(kind='bar', color='orange')
# Setting the title, x-axis label, and y-axis label
plt.title('Average Socioeconomic Status by Country')
plt.xlabel('Country')
plt.ylabel('Average Socioeconomic Status')
# Rotating x-axis labels for better readability
plt.xticks(rotation=45, ha="right");
The bar chart ranks countries by their average socioeconomic status.¶
How does average reading performance compare between genders across different countries?¶
In [ ]:
# Grouping data by 'Country' and 'Male' and calculating the average reading performance
average_reading_by_gender_country = pisa2012clean.groupby(['Country', 'Male'])['Reading'].mean().unstack()
# Sorting the data based on the specified order
average_reading_by_gender_country = average_reading_by_gender_country.loc[order]
# Plotting the bar chart
average_reading_by_gender_country.plot(kind='bar', figsize=(25, 8), color=['orange','blue'])
# Setting the title, x-axis label, and y-axis label
plt.title('Average Reading Performance by Gender and Country')
plt.xlabel('Country')
plt.ylabel('Average Reading Performance')
# Rotating x-axis labels for better readability
plt.xticks(rotation=45, ha="right")
# Adding legend
plt.legend(title='Gender', labels=['Female', 'Male']);
It shows a side-by-side comparison of male and female reading performance averages for each country.¶
What is the gender distribution among participants?¶
In [ ]:
# Counting the distribution of genders
gender_counts = pisa2012clean['Male'].value_counts()
# Plotting the pie chart
plt.figure(figsize=(6, 6))
plt.pie(gender_counts, labels=['Female', 'Male'], autopct='%1.1f%%', startangle=90, colors=['orange','blue'])
# Setting the title for the plot
plt.title('Gender Distribution of Participants');
It's a pie chart illustrating the percentage of male and female participants, indicating a nearly even split.¶
What is the cumulative distribution of socioeconomic status among participants?¶
In [ ]:
# Create a figure with a specific size
plt.figure(figsize=(6, 6))
# Plot a cumulative histogram of 'Socioeconomic' pisa2012clean
sb.histplot(pisa2012clean['Socioeconomic'], bins=30, cumulative=True, element="step", fill=False, color='navy')
# Set title, x-axis label, and y-axis label
plt.title('Cumulative Distribution of Socioeconomic Status')
plt.xlabel('Socioeconomic Status')
plt.ylabel('Cumulative Number of Participants');
It shows how the socioeconomic status of participants accumulates across the range of status levels.¶
How many participants are there from each country in this study?¶
In [ ]:
plt.figure(figsize=(25, 8))
# Plotting countplot with x and y axes swapped and applying order to countries
sb.countplot(x='Country', data=pisa2012clean, order=order, color='blue')
# Setting plot title, labels, and displaying the plot
plt.title('Number of Participants by Country')
plt.xlabel('Country')
plt.ylabel('Number of Participants')
plt.xticks(rotation=45, ha="right");
It displays the number of participants from various countries, with some countries having significantly higher numbers of participants than others.¶
What is the percentage of male and female participants in each country?¶
In [ ]:
# Group pisa2012clean by 'Country' and calculate percentage distribution of 'Male' values
gender_distribution_per_country = pisa2012clean.groupby('Country')['Male'].value_counts(normalize=True).unstack().fillna(0) * 100
# Reorder the rows based on the specified order
gender_distribution_per_country = gender_distribution_per_country.loc[order]
# Plotting
gender_distribution_per_country.plot(kind='bar', stacked=True, color=['orange','blue'], figsize=(25, 8))
# Setting plot title, labels, and legend
plt.title('Percentage of Male and Female Participants by Country')
plt.xlabel('Country')
plt.ylabel('Percentage')
plt.xticks(rotation=45, ha="right")
plt.legend(title='Gender', labels=['Female', 'Male']);
Each bar represents a country with proportions of male and female participants stacked on top of each other, showing gender distribution across countries.¶
In [ ]:
def plot_average_total_score():
# Calculating mean total scores for males and females by country
male_mean = pisa2012clean.query("Male == 1").groupby('Country')['Total'].mean()
female_mean = pisa2012clean.query("Male == 0").groupby('Country')['Total'].mean()
# Setting up y-axis ticks
ybins = np.arange(10, 900 + 20, 20)
yticks = ybins[::1] - 10
# Creating the plot
fig, ax1 = plt.subplots(figsize=(25, 10))
plt.yticks(yticks)
plt.xticks(rotation=60, ha='right')
# Boxplot showing the interquartile range (IQR)
sb.boxplot(data=pisa2012clean, x='Country', y='Total', order=order, showfliers=False, whis=0, color='lightgray', ax=ax1, width=.5, linewidth=.5)
# Adding gridlines
plt.grid(True, linestyle='--', linewidth=.3)
# Plotting average markers for each country
for i, country in enumerate(order):
mean_val = Total_mean[country]
mean_val_male = male_mean[country]
mean_val_female = female_mean[country]
ax1.plot(i, mean_val_male, marker='o', color='blue', markersize=8)
ax1.plot(i, mean_val_female, marker='o', color='orange', markersize=8)
ax1.plot(i, mean_val, marker='x', color='black', markersize=8)
# Setting labels and title
ax1.set_ylabel('Total Scores', fontsize=16)
ax1.set_xlabel('')
plt.title('Total Scores: IQR with Avg. Markers by Countries', fontsize=24)
# Adding legend
legend_labels = ['Total Avg.', 'Male Avg.', 'Female Avg.']
legend_handles = [plt.Line2D([0], [0], marker='x', color='black', markersize=24, linestyle='None'),
plt.Line2D([0], [0], marker='o', color='blue', markersize=24, linestyle='None'),
plt.Line2D([0], [0], marker='o', color='orange', markersize=24, linestyle='None')]
plt.legend(legend_handles, legend_labels, fontsize=24)
What is the distribution of total scores among participants, and how does the average score differ by gender across countries?¶
In [ ]:
plot_average_total_score()
The box plots show the interquartile range (IQR) of total scores in various countries, with markers indicating the average scores for males and females.¶
In [ ]:
def plot_score_distribution(pisa_2012_clean, Subjects):
# Create a figure with appropriate size
plt.figure(figsize=[25, 1+9/len(Subjects)])
# Define bin edges for x and y axes
xbins = np.arange(10, 900 + 20, 20)
ybins = np.arange(0, .0042 + .0002, .0002)
# Define tick locations for x and y axes
xticks = xbins[::len(Subjects)] - 10
yticks = ybins[::len(Subjects)]
# Iterate over each subject and plot the distribution by gender
for col_index, Subject in enumerate(Subjects):
ax = plt.subplot(1, len(Subjects), col_index + 1)
# Plot kernel density estimate (KDE) for male and female scores
sb.kdeplot(data=pisa_2012_clean[pisa_2012_clean['Male'] == 1][Subject], label='Male', color='blue', ax=ax)
sb.kdeplot(data=pisa_2012_clean[pisa_2012_clean['Male'] == 0][Subject], label='Female', color='orange', ax=ax)
# Set tick locations and labels for x and y axes
ax.set_xticks(xticks)
ax.set_yticks(yticks)
ax.set_xticklabels(xticks, rotation=15)
ax.set_yticklabels((yticks*1000).round(1))
# Add grid lines and set axis limits
ax.grid(axis='y', linestyle='--', alpha=.5)
ax.set_xlim(0, 910)
ax.set_ylim(0, .0042)
# Set title, x-axis label, and y-axis label
ax.set_title(Subject, fontsize=16)
ax.set_xlabel(f'{Subject} Scores', fontsize=16)
ax.set_ylabel('Parts per thousand' if col_index == 0 else '', fontsize=16)
# Add legend
ax.legend(loc='lower center', fontsize=8+24/len(Subjects))
# Set super title
plt.suptitle(f'Distribution of Student Scores {"across Subjects " if Subjects != ["Total"] else ""}by Gender', fontsize=24, y=.89+len(Subjects)/18)
What is the distribution of student scores by gender?¶
In [ ]:
plot_score_distribution(pisa2012clean, Subjects=['Total'])
The plot compares the distribution curves for male and female participants, showing where scores are most concentrated.¶
How are student scores distributed across different subjects by gender?¶
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plot_score_distribution(pisa2012clean, Subjects)
There are separate density plots for math, reading, and science scores, each comparing the score distributions for male and female students.¶
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def plot_dependent_distribution(pisa_2012_clean, Subjects, Dependencies):
# Create subplots grid
fig, axs = plt.subplots(len(Dependencies), len(Subjects), figsize=(25, 12), squeeze=False)
# Define bins and xticks
bins = np.arange(10, 900 + 20, 20)
xticks = bins[::len(Subjects)] - 10
# Iterate over rows and columns
for row_index, Dependency in enumerate(Dependencies):
for col_index, Subject in enumerate(Subjects):
# Add jitter to the dependent variable
jittered_dependent = pisa_2012_clean[Dependency] + np.random.uniform(-.35, .35, size=len(pisa_2012_clean))
# Calculate correlation coefficient
correlation = pisa_2012_clean[Subject].corr(pisa_2012_clean[Dependency])
# Create hexbin plot
hb = axs[row_index, col_index].hexbin(pisa_2012_clean[Subject], jittered_dependent, bins='log', vmin=1, vmax=2000)
# Customize x-axis
axs[row_index, col_index].set_xticks(xticks)
axs[row_index, col_index].set_xticklabels(xticks, rotation=15)
axs[row_index, col_index].set_xlim(0, 910)
# Add correlation coefficient text
axs[row_index, col_index].text(.84, .02, f'ρ = {correlation:.2f}', transform=axs[row_index, col_index].transAxes, fontsize=54/len(Subjects)-4)
# Set title, x-axis label, and y-axis label
axs[row_index, col_index].set_title(f'{Subject} | {Dependency}', fontsize=10)
axs[row_index, col_index].set_xlabel(f'{Subject} Scores' if row_index == len(Dependencies)-1 else '', fontsize=16)
axs[row_index, col_index].set_ylabel(f'{Dependency} Index' if col_index == 0 else '', fontsize=16)
# Add colorbar
cbar_ax = fig.add_axes([.91, .11 + row_index * .272, .01, (.815 / len(Dependencies))-.045])
cbar = fig.colorbar(hb, cax=cbar_ax)
cbar.set_ticks([1, 2, 5, 10, 20, 50, 100, 200, 500, 1000, 2000])
cbar.ax.yaxis.set_major_formatter(ScalarFormatter())
cbar.set_label('Frequency', fontsize=16)
# Add overall title
plt.suptitle(f'Distribution of Student Scores {(Subjects != ["Total"]) * "across Subjects "}depending on Parental Factors{(Dependencies == ["Socioeconomic"]) * " together"}', fontsize=24, y=.93)
What is the relationship between student scores and their socioeconomic background?¶
In [ ]:
plot_dependent_distribution(pisa2012clean, Subjects=["Total"], Dependencies=["Socioeconomic"])
This hexbin plot shows concentrations of student scores against socioeconomic index, with a color density indicating the frequency of scores. The correlation coefficient (ρ) suggests the strength of the relationship.¶
How do parental factors such as education, occupation, and home setup influence student scores across different subjects?¶
In [ ]:
plot_dependent_distribution(pisa2012clean, Subjects, Dependencies)
Each scatter plot shows student scores against different parental indices for math, reading, and science. Correlation coefficients are provided for each factor's relationship with the scores.¶
In [ ]:
pisadict2012clean.T.to_csv('./data/pisadict2012clean.csv')
pisa2012clean.to_csv('./data/pisa2012clean.csv', index=False)